Real-Time Distributed Cloud Computing Architecture for Structural Health Monitoring
Real-Time Distributed Cloud Computing Architecture for Structural Health Monitoring
复制标题
用于结构健康监测的实时分布式云计算架构
DOI:
10.1061/9780784482230.005
复制
发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Sanayei, Masoud
中科院分区:
文献类型:
--
作者:
Searls, Owen;Zhao, Zhiyong;Couch, Alva L.;Sanayei, Masoud
Real-time fatigue health monitoring has the potential to serve as a valuable complement to structural health monitoring (SHM) for bridge inspections. SHM is an objective supplement to visual bridge inspections with a minimum interval between bridge inspections at 24 months. SHM can provide quantitative and objective data on a bridge’s fatigue condition for fracture-critical components, of which fatigue is a criterion. Current methods of continuous structural health monitoring for condition assessment are performed by collecting measured bridge response subjected to operational traffic from an array of sensors installed on fracture-critical members of a bridge. The measured responses are used to determine the remaining fatigue life of the bridge—the minimum time before repair. The large amount of data involved in this process complicates the design of a system that will automate the data collection process at a bridge, analyze that data, and display information about bridge health to researchers and engineers. Variations in bridge designs and condition assessment algorithms also necessitate that such a system be modular and adaptable to allow for expansion to additional structures. A new system has been developed that separates bridge SHM from the data storage and communication system. This architecture creates a reliable interface for sending data from one or more bridges to a cloud server where it can be processed using modular algorithms that can be adapted for different use cases. The cloud-based web service and data repository makes bridge structural health data available to researchers at all steps of the process. This system provides significant advantages over previous platforms for structural health monitoring and condition assessment, most notably in the areas of modularity, extensibility, and reliability.
影响因子:
3.6
作者:
Jordan C. Weinstein;M. Sanayei;B. Brenner
通讯作者:
Jordan C. Weinstein;M. Sanayei;B. Brenner
DOI:
--
发表时间:
2017
期刊:
影响因子:
--
作者:
Zhiyong Zhao
通讯作者:
Zhiyong Zhao
影响因子:
3.6
作者:
Saberi, Mohammad Reza;Rahai, Ali Reza;Vogel, Richard M.
通讯作者:
Vogel, Richard M.